Plot of observed vs. predicted EQ5D utilities for candidate full models. by Rahul Khairnar (8906282)

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Bland-Altman plot for full candidate model using EPIC sub-domain data. by Rahul Khairnar (8906282)

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Highly Accurate Prediction of Core Spectra of Molecules at Density Functional Theory Cost: Attaining Sub-electronvolt Error from a Restricted Open-Shell Kohn–Sham Approach by Diptarka Hait (2835971)

Subjects:

Highly Accurate Prediction of Core Spectra of Molecules at Density Functional Theory Cost: Attaining Sub-electronvolt Error from a Restricted Open-Shell Kohn–Sham Approach by Diptarka Hait (2835971)

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Data extraction and patient algorithm. by Jennifer M. Kwan (3350321)

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement by Antoine Falisse (6061601)

“…<div><p>Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. …”

Swarm intelligence algorithms for width and length on influence games by Francisco Muñoz (9455441)

“…<br><br><div>usage: Main.py [-h] [-a] [-r] [-d D] [-t T] [-i I] [-q Q] [--shape SHAPE] [--sym] [--folder FOLDER] [--seed SEED] [--sum SUM] [--mh MH] [--tagsfile TAGSFILE] [--notags] [--prune] [--excludenodes EXCLUDENODES]<br><br>Calculates the best Influence Spread set on a Weighted Symmetric Graph using PSO<br></div><div><br></div><div><div>positional arguments:</div><div> file</div><div><br></div><div>optional arguments:</div><div> -h, --help: show this help message and exit</div><div> -a: threat file input contents as an Adjacency Matrix</div><div> -r: reverse order of nodes, from (a,b,w) a -> b will be b -> a</div><div> -d D: line separator to use while parsing</div><div> -t T: number of times to execute</div><div> -i I: number of metaheuristic iterations per execution</div><div> -q Q: fixed quota, use 0 = floor(n/2)+1</div><div> --shape SHAPE: shape functions for binarization - list of implemented shape functions: s2,s2_neg,v2,v4</div><div> --sym: consider graph as symmetric instead of directed</div><div> --folder FOLDER: output folder</div><div> --seed SEED: use custom seed for metaheuristic calcs</div><div> --sum SUM: adds a value to all node labels</div><div> --mh MH: metaheuristic to use - list of implemented metaheuristics: {1: 'Swarm', 2: 'Swarm2', 3: 'Swarm_W', 4:</div><div> 'Swarm_L'}</div><div> --tagsfile TAGSFILE: use first row as node tags instead of using plurality criteria</div><div> --notags: do not use first row as node tags - tags will be calculated</div><div> --prune: nodes with outdegree = 0 and indegree > 0, and with outdegree = 1 and neighbor's outdegree > 0 will be excluded</div><div> --excludenodes EXCLUDENODES: nodes to skip, comma separated</div></div>…”

Supervised Predictive Modeling of High-dimensional Data with Group l0-norm Constrained Neural Networks by Zhihuang Yang (22530437)

“…By leveraging group <math><mrow><msub><mrow><mi>l</mi></mrow><mn>0</mn></msub></mrow></math>-norm constrained neural networks, the proposed approach aims to simultaneously extract crucial features and estimate the underlying model function with statistically guaranteed accuracy. …”

Adaptive grid based moving mesh algorithms for singularly perturbed second-order Volterra integro differential equations by Sushree Priyadarshana (21752424)

“…<p>Robust adaptive grid-based moving mesh algorithms are discussed for singularly perturbed second-order convection-diffusion type Volterra integro differential equations. …”

Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

Cooperativity and nonlinear amplification of synaptic input in cell type specific models. by Daniele Linaro (227790)

Subjects: “…biophysically detailed models…”

Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

Subjects: “…biophysically detailed models…”

FLIM observation model. by Daniel U. Campos-Delgado (10325866)

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CEL0, and to a lesser extent, <i>ℓ</i>_1/2, and hard thresholding produce sparser codes than ISTA. by Ilias Rentzeperis (10215602)

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Compare the test functions. by Yanqiu Li (683621)

Convergence curves of different algorithms on the benchmark functions. by Aihua Guo (13267712)

G-clusteron model and synaptic location update rule. by Toviah Moldwin (10866708)

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Results of searching performance of different algorithm models on the Sphere function and Griewank function. by Rui Zhang (13940)

“…<p>Results of searching performance of different algorithm models on the Sphere function and Griewank function.…”

Robotic Prototype with Human Mimicry Abilities - 104 Algorithms (RPHMA^104a): Toward an Integrative Computational-Robotic Theory of Very Complex Skills by Maicon S. Aliaga Machado (20468810)

“…<p dir="ltr"><b>Abstract</b></p><p dir="ltr">This paper introduces the RPHMS^104a model (Robotic Prototype with Human Mimicry Abilities - 104 Algorithms), a framework for the progressive development of artificial systems capable of emulating human cognitive-behavioral functions. …”